Data Analytics and Market Sensing

From robots and artificial intelligence taking root in the workplace to the coming of age of the Internet of Things (IoT) and Big Data getting bigger, business can expect to see disruptions in industries, sectors and markets. Globalization and the rapid commoditization of goods and services have laid the ground for far more intense disruptions, and no sector or industry or market will be immune to these changes.

Technology will continue to lead the disruption with the coming of age of fields like quantum computing, augmented and virtual reality, blockchains, robotics, etc. New business models will evolve and new businesses will be created, many of which will be involved in the field of advanced manufacturing. For example, smart systems (solutions that incorporate functions of sensing, actuation, and control in order to describe and analyze a situation, and make decisions based on the available data in a predictive or adaptive manner, thereby performing smart actions) will be rolled out to maximize the use of resources, increase productivity and improve business operations.

Many, if not all, businesses will have to adapt to the changes that is happening in their companies. Many will have to embrace the changes, accept that business models and processes have to be responsive and that employees at all level need to work differently and be vested in its growth and development. Employees will have to change for change sake as they are an essential part of the new normal, for example, as systems become more “sensing”, so too must the employees and the company as a whole. Those that are not adapting and changing will find it hard to remain relevant.

Objectives

The integration of technology in processes or operations in advanced manufacturing is not limited to the use of automation and robotics to gain competitive advantages; it includes the use of existing technologies and approaches, e.g. data analytics, real-time monitoring solutions, people management systems, etc. Companies remain competitive through many means and empirical evidence shows that a successful company has an uncanny ability to come up with products and service at the right time and a management team that is able to adapt to changes and is great at implementation.

The objective of this course is to enable companies that serve the advanced manufacturing sector to be more “sensing”, i.e. being able to seek out opportunities and anticipate threats using sensing tools and methods like data analysis, benchmarking, etc. Quoting Peter Drucker, “What a business needs most for its decisions — especially its strategic ones — are data about what goes on outside it. Only outside a business are there results, opportunities and threats.”

Outline

There are two parts to this course:

• The first part will introduce participants to data analysis, data analytics and business intelligence solutions and approaches. Participants will learn about different “sensing” tools and methods, and how to incorporate them into their day-to-day operations. “Sensing” tools include data analysis and analytics, business intelligence (i.e. market, competitor and customer intelligence) gathering methods, information distribution channels, benchmarking techniques, and many more.

• The second part will look at managing the “disruption” within the company. Making a company or organization more “sensing”, will involve everyone in the organization, from the receptionist using prepared FAQs and taking feedback from customers to the sales person in the field pitching the company’s products to gathering business intelligence for the corporate network. Getting employees to change and embrace new technologies, and be more sensing will raise new business and operational challenges. The challenge for management will be even greater, not just because the company is embracing new technologies and solutions, but in managing its employees behaviour and expectations in a changed working environment. As companies navigate a more chaotic, and even uncharted, environment, management and staff need new skills to remain relevant. Some of these include:

• Understanding new technologies and how to leverage on them.

• Managing expectations and change in the organization.

• Understanding stakeholder’s needs, in particular their Customers.

• Implement and manage knowledge systems, e.g. a Business Intelligence and Data Analytics solutions.

• Understanding different business models.

Through the use of lectures, case studies and group work, participants will understand the different approaches and internalize them.